Atmospheric Suspended Particles Research Articles

Influence of space electromagnetic radiation on physical characteristics of atmospheric suspended micro particles

In recent years, researchers from various countries have found that atmospheric microparticle pollution occurring around the world has seriously endangered human health and the earth’s ecological environment. In order to solve the problem of atmospheric micro-particle pollution, researchers have carried out multi-faceted analysis on its source, composition and causes of pollution. However, few people combine the complex electromagnetic environment in space with the problem of micro-particle pollution in recent years. In this study, it is found that atmospheric suspended microparticles have weak magnetism and carry charge, so it is preliminarily explored whether space electromagnetic radiation has an effect on microparticles. Based on this background, this study used simulation modeling and experimental verification methods. The results show that the physical properties of atmospheric suspended microparticles will be significantly changed by electromagnetic radiation.

Effect of mixed magnetic field on physical properties of atmospheric suspended fine particles

In recent years, the fine particles suspended in the atmosphere, especially the particle size less than 10 μm, have caused very adverse effects on the climate environment and human health. However, the current research on the causes of air pollution mainly focuses on human activities and weather conditions. Considering the weak magnetism and chargeability of atmospheric fine particles, this study proposed a new view that space electromagnetic radiation may affect the physical properties of fine particles. We first analyzed the dynamic characteristics of magnetic micro-particle in the electromagnetic environment, and built a simulation model in the COMSOL simulation software. Finally, based on the theoretical analysis and simulation results, we built an experimental verification system to evaluate the effects of electromagnetic radiation on the physical properties of micro-particle, and carried out a 30-day control experiment. The experimental results showed that the physical properties such as particle size distribution, mass concentration, and morphology of suspended fine particles in the atmosphere under electromagnetic radiation are significantly different from those under non-electromagnetic radiation environment. It can be inferred that the aggregation, fusion, and deposition of suspended particles in the atmosphere are closely related to the complex electromagnetic environment in space.

Multivariate Urban Air Quality Assessment of Indoor and Outdoor Environments at Chennai Metropolis in South India

The present study examines indoor and outdoor environmental particulate matter and gaseous pollutants in order to evaluate the urban air quality, the sources and pathways of pollutants, and its impact on Chennai megacity, South India. A total number of 25 air conditioner filter particulate matter samples collected from residential buildings, schools, colleges, commercial shopping malls, and buildings near urban highways were studied for indoor air quality. Similarly, outdoor air quality assessments have been done in various parts of the Chennai metropolis, including the Manali-Industrial area, the Velachery-Residential site, and the Alandur Bus Depot, as well as collected air quality data sets from the Central Pollution Control Board at continuous ambient air quality monitoring stations. The suspended atmospheric particles where the highest concentration (47%) occurred were mostly located in the roadside environments followed by commercial areas (42%), which indicates the increase in air pollution in the roadside areas. Further, environmental magnetism and ecological risk indices were studied from the collected data set. The study predicts that the air pollutants were predominantly from anthropogenic sources, such as vehicle emissions, effluents from power plants, abrasion of tires, steelworks, burning of fossil fuels and construction materials, etc. As a result, the current study suggests 68% of indoor pollutants were from the anthropogenic input, 18% from the pedogenic origin, and 14% from high heavy metal pollution at the sampling sites. This indicates that raising the ventilation rate via mechanical components significantly enhances the indoor air quality. These findings might be valuable in improving urban air quality, reducing traffic-related pollutants, and improving environmental quality.

The Research of GIS Discharge Influence Based on Particle Properties in Installation Environment

In order to explore the influence of atmospheric free particles that exit during GIS installation on the stable operation of GIS, the size, shape and inner properties of the particles contained in the air are analyzed. And based on 500kV GIS equipment, the GIS gas chamber model and the model of free particles were established. By using the finite element simulation software, the surface electric field distribution when the free particles remain on the insulator surface is solved. The results show that the electric field distribution of particles which exist along the surface of insulator is directly related to the relative permittivity of the material of the particles themselves, and the intensity of the electric field along the surface increases with the increase of the relative permittivity. with the fact that the relative permittivity of air particles is almost below 20, as a result, the existence of 10µm grade non-metallic free particles will not cause flashover discharge. But, when a small number of Fe3O4 particles which size over 1mm or when them accumulate regularly, it will lead to flashover discharge. Therefore, the suspended atmospheric particles in the installation environment have little impact on the stable operation of GIS. When considering the installation environmental conditions, the installation can be carried out on a clear, windless day which can save costs.

Light-DehazeNet: A Novel Lightweight CNN Architecture for Single Image Dehazing.

Due to the rapid development of artificial intelligence technology, industrial sectors are revolutionizing in automation, reliability, and robustness, thereby significantly increasing quality and productivity. Most of the surveillance and industrial sectors are monitored by visual sensor networks capturing different surrounding environment images. However, during tempestuous weather conditions, the visual quality of the images is reduced due to contaminated suspended atmospheric particles that affect the overall surveillance systems. To tackle these challenges, this article presents a computationally efficient lightweight convolutional neural network referred to as Light-DehazeNet (LD-Net) for the reconstruction of hazy images. Unlike other learning-based approaches, which separately measure the transmission map and the atmospheric light, our proposed LD-Net jointly estimates both the transmission map and the atmospheric light using a transformed atmospheric scattering model. Furthermore, a color visibility restoration method is proposed to evade the color distortion in the dehaze image. Finally, we conduct extensive experiments using synthetic and natural hazy images. The quantitative and qualitative evaluation on different benchmark hazy datasets verify the superiority of the proposed method over other state-of-the-art image dehazing techniques. Moreover, additional experimentation validates the applicability of the proposed method in the object detection tasks. Considering the lightweight architecture with minimal computational cost, the proposed system is encouraged to be incorporated as an integral part of the vision-based monitoring systems to improve the overall performance.

Using a Hybrid of Interval Type-2 RFCMAC and Bilateral Filter for Satellite Image Dehazing

With increasing advancement of science and technology, remote sensing satellite imaging does not only monitor the Earth’s surface environment instantly and accurately but also helps to prevent destruction from inevitable disasters. The changing weather, e.g., cloudiness or haze formed from atmospheric suspended particles, results in low contrast satellite images, and partial information about Earth’s surface is lost. Therefore, this study proposes an effective dehazing method for one single satellite image, aiming to enhance the image contrast and filter out the region covered with haze, so as to reveal the lost information. First, the initial transmission map of the image is estimated using an Interval Type-2 Recurrent Fuzzy Cerebellar Model Articulation Controller (IT2RFCMAC) model. For the halo and color oversaturation resulted from the processing procedure, a bilateral filter and quadratic function nonlinear conversion are used in turn to refine the initial transmission map. For the estimation of atmospheric light, the first 1% brightest region is used as the color vector of atmospheric light. Finally, the refined transmission map and atmospheric light are used as the parameters for reconstructing the image. The experimental results show that the proposed satellite image dehazing method has good performance in the visibility detail and color contrast of the reconstructed image. In order to further validate the effectiveness of the proposed method, visual assessment and quantitative evaluation were implemented, respectively, and compared with the methods proposed by relevant scholars. The visual assessment and quantitative evaluation analysis demonstrated good results of the proposed approach.

Regulation by thiol disulfide and antioxidant systems of oxidative stress induced by atmospheric suspended particles

Regulation by thiol disulfide and antioxidant systems of oxidative stress induced by atmospheric suspended particles

PDR-Net: Perception-Inspired Single Image Dehazing Network With Refinement

During recent years, we have witnessed a rapid development of wireless network technologies which have revolutionized the way people take and share multimedia content. However, images captured in the outdoor scenes usually suffer from limited visibility due to suspended atmospheric particles, which directly affects the quality of photos. Despite the recent progress of image dehazing methods, the visual quality of dehazed results still needs further improvement. In this paper, we propose a deep convolutional neural network (CNN) for single image dehazing called PDR-Net, which includes a perception-inspired haze removal subnetwork that reconstructs the latent dehazed image and a refinement subnetwork that further enhances the contrast and color properties of the dehazed result by joint multi-term loss optimization. Compared to the previous methods, our method combines the advantages of existing indoor and outdoor image dehazing training data, which makes the proposed PDR-Net generalized to various hazy images and effective for improving the visual quality of the dehazed results. Extensive experiments demonstrate that the proposed method achieves comparable and even better performance on both real and synthetic images in qualitative and quantitative metrics. Additionally, the potential usage of our method in high-level vision tasks is discussed.

Simultaneous determination of neutral sugars, alditols and anhydrosugars using anion-exchange chromatography with pulsed amperometric detection: Application for marine and atmospheric samples

An improved high-performance anion-exchange chromatography with pulsed amperometric detection (HPAEC-PAD) method is described for the simultaneous determination of neutral sugars (hexoses, pentoses and deoxysugars), alditols and anhydrosugars commonly found in atmospheric and marine samples. The method uses a CarboPac MA1 column, at a flow rate of 0.3 mL min−1, and a NaOH gradient (250–700 mM). The proposed method applies a temperature gradient (from 25 to 28 °C) to the column for the first 30 min of the analysis, followed by a constant temperature at 28 °C until the end of the analysis. These analytical conditions allowed the separation of 15 out of 17 carbohydrates in 75 min with resolution factors better than 0.5 for the critical pairs levoglucosan/arabitol, galactosan/arabinose, arabinose/mannose and glucose/xylose.The application of this method to field samples revealed that anhydrosugars represented 53% of total neutral carbohydrates (TCHO) in total suspended atmospheric particles (TSP), whereas they were detected for the first time in marine particulate organic matter (POM) and high-molecular-weight dissolved organic matter (HMWDOM) samples accounting 2% and 3% of TCHO, respectively. Levoglucosan and/or galactosan were the major anhydrosugars in all samples however, their concentrations are undoubtedly underestimated because hydrolysis was applied to the marine samples prior to the HPAEC-PAD analysis. Despite this underestimation, their presence in the marine samples clearly indicates possible terrestrial input most likely via atmospheric deposition as these compounds are considered terrestrial burring biomass tracers. Finally, deoxysugars were also detected for the first time in the TSP sample representing 1% of TCHO, while alditols accounted for 0.4% and 0.3% of TCHO in POM and HMWDOM, respectively.

Liquid chromatographic isolation of individual carbohydrates from environmental matrices for stable carbon analysis and radiocarbon dating

Carbohydrates are among the most abundant organic molecules in both aquatic and terrestrial ecosystems; however, very few studies have addressed their isotopic signature using compound-specific isotope analysis, which provides additional information on their origin (δ13C) and fate (Δ14C). In this study, semi-preparative liquid chromatography with refractive index detection (HPLC-RI) was employed to produce pure carbohydrate targets for subsequent offline δ13C and Δ14C isotopic analysis. δ13C analysis was performed by elemental analyzer-isotope ratio mass spectrometer (EA-IRMS) whereas Δ14C analysis was performed by an innovative measurement procedure based on the direct combustion of the isolated fractions using an elemental analyzer coupled to the gas source of a mini carbon dating system (AixMICADAS). In general, four successive purifications with Na+, Ca2+, Pb2+, and Ca2+ cation-exchange columns were sufficient to produce pure carbohydrates. These carbohydrates were subsequently identified using mass spectrometry by comparing their mass spectra with those of authentic standards.The applicability of the proposed method was tested on two different environmental samples comprising marine particulate organic matter (POM) and total suspended atmospheric particles (TSP). The obtained results revealed that for the marine POM sample, the δ13C values of the individual carbohydrates ranged from −18.5 to −16.8‰, except for levoglucosan and mannosan, which presented values of −27.2 and −26.2‰, respectively. For the TSP sample, the δ13C values ranged from −26.4 to −25.0‰. The galactose and glucose Δ14C values were 19 and 43‰, respectively, for the POM sample. On the other hand, the levoglucosan radiocarbon value was 33‰ for the TSP sample. These results suggest that these carbohydrates exhibit a modern age in both of these samples. Radiocarbon HPLC collection window blanks, measured after the addition of phthalic acid (14C free blank), ranged from −988 to −986‰ for the abovementioned compounds, indicating a very small background isotopic influence from the whole purification procedure. Overall, the proposed method does not require derivatization steps, produces extremely low blanks, and may be applied to different types of environmental samples.

Total dissolved atmospheric nitrogen deposition in the anoxic Cariaco basin

Atmospheric deposition of total dissolved nitrogen (TDN) is an important source of nitrogen for ocean primary productivity that has increased since the industrial revolution. Thus, understanding its role in the ocean nitrogen cycle will help assess recent changes in ocean biogeochemistry. In the anoxic Cariaco basin, the place of the CARIACO Ocean Time-Series Program, the influence of atmospherically-deposited TDN on marine biogeochemistry is unknown. In this study, we measured atmospheric TDN concentrations as dissolved organic (DON) and inorganic (DIN) nitrogen (TDN = DIN + DON) in atmospheric suspended particles and wet deposition samples at the northeast of the basin during periods of the wet (August–September 2008) and dry (March–April 2009) seasons. We evaluated the potential anthropogenic N influences by measuring wind velocity and direction, size-fractionated suspended particles, chemical traces and by performing back trajectories. We found DIN and DON concentration values that ranged between 0.11 and 0.58 μg-N m−3 and 0.11–0.56 μg-N m−3 in total suspended particles samples and between 0.08 and 0.54 mg-N l−1 and 0.02–1.3 mg-N l−1 in wet deposition samples, respectively. Continental air masses increased DON and DIN concentrations in atmospheric suspended particles during the wet season. We estimate an annual TDN atmospheric deposition (wet + particles) of 3.6 × 103 ton-N year−1 and concluded that: 1) Atmospheric supply of TDN plays a key role in the C and N budget of the basin because replaces a fraction of the C (20% by induced primary production) and N (40%) removed by sediment burial, 2) present anthropogenic N could contribute to 30% of TDN atmospheric deposition in the basin, and 3) reduced DON (gas + particles) should be a significant component of bulk N deposition.

A Cascaded Convolutional Neural Network for Single Image Dehazing

Images captured under outdoor scenes usually suffer from low contrast and limited visibility due to suspended atmospheric particles, which directly affects the quality of photos. Despite numerous image dehazing methods have been proposed, effective hazy image restoration remains a challenging problem. Existing learning-based methods usually predict the medium transmission by Convolutional Neural Networks (CNNs), but ignore the key global atmospheric light. Different from previous learning-based methods, we propose a flexible cascaded CNN for single hazy image restoration, which considers the medium transmission and global atmospheric light jointly by two task-driven subnetworks. Specifically, the medium transmission estimation subnetwork is inspired by the densely connected CNN while the global atmospheric light estimation subnetwork is a light-weight CNN. Besides, these two subnetworks are cascaded by sharing the common features. Finally, with the estimated model parameters, the haze-free image is obtained by the atmospheric scattering model inversion, which achieves more accurate and effective restoration performance. Qualitatively and quantitatively experimental results on the synthetic and real-world hazy images demonstrate that the proposed method effectively removes haze from such images, and outperforms several state-of-the-art dehazing methods.

Robust Dehaze Algorithm for Degraded Image of CMOS Image Sensors.

The CMOS (Complementary Metal-Oxide-Semiconductor) is a new type of solid image sensor device widely used in object tracking, object recognition, intelligent navigation fields, and so on. However, images captured by outdoor CMOS sensor devices are usually affected by suspended atmospheric particles (such as haze), causing a reduction in image contrast, color distortion problems, and so on. In view of this, we propose a novel dehazing approach based on a local consistent Markov random field (MRF) framework. The neighboring clique in traditional MRF is extended to the non-neighboring clique, which is defined on local consistent blocks based on two clues, where both the atmospheric light and transmission map satisfy the character of local consistency. In this framework, our model can strengthen the restriction of the whole image while incorporating more sophisticated statistical priors, resulting in more expressive power of modeling, thus, solving inadequate detail recovery effectively and alleviating color distortion. Moreover, the local consistent MRF framework can obtain details while maintaining better results for dehazing, which effectively improves the image quality captured by the CMOS image sensor. Experimental results verified that the method proposed has the combined advantages of detail recovery and color preservation.

An index for estimating the potential metal pollution contribution to atmospheric particulate matter from road dust in Beijing

The resuspension of road dust from street surfaces could be a big contributor to atmospheric particulate pollution in the rapid urbanization context in the world. However, to date what its potential contribution to the spatial pattern is little known. Here we developed an innovative index model called the road dust index (RI<105μm) and it combines source and transport factors for road dust particles <105μm in diameter. It could quantify and differentiate the impact of the spatial distribution of the potential risks posed by metals associated with road dust on atmospheric suspended particles. The factors were ranked and weighted based on road dust characteristics (the amounts, grain sizes, and mobilities of the road dust, and the concentrations and toxicities of metals in the road dust). We then applied the RI<105μm in the Beijing region to assess the spatial distribution of the potential risks posed by metals associated with road dust on atmospheric suspended particles. The results demonstrated that the road dust in urban areas has higher potential risk of metal to atmospheric particles than that in rural areas. The RI<105μm method offers a new and useful tool for assessing the potential risks posed by metals associated with road dust on atmospheric suspended particles and for controlling atmospheric particulate pollution caused by road dust emissions.

Distribution of PBDEs in Atmospheric Total Suspended Particles Collected from Kunming, China

An efficient and reliable analytical method has been used for determination of polybrominated diphenyl ethers (PBDEs) in atmospheric total suspended particles collected from the six state controlling air sampling sites and two self-selection sampling sites in Kunming, China. The results showed that the overall average concentrations of TSP collected from Kunming were in the range of 44.36 μg/m3 to 82.22 μg/m3. This pattern was lower than the average concentrations of Guiyu, Guangzhou and similar to Hong Kong. In TSP, the penta-BDEs and octa-BDEs were the dominant PBDEs and the PBDEs concentration ranged from 12.39 pg/m3 to 71.51 pg/m3, with a mean value of 46.82 pg/m3. This level was below the city of Guiyu, Örebro in Sweden and similar to Hong Kong, Guangzhou. The average concentrations of PBDEs had the trend of descent from the urban center to the outskirts of Kunming.

Different chemical properties of lead in atmospheric particles from urban roadside and residential areas

Lead in atmospheric suspended particles was fractionized using simple acid extraction to assess differences in chemical properties of lead from roadside and residential areas. The Pb–LIII edge XANES measurement was also challenged to explore the possibilities of contamination from road dust into the air. Results suggest that 0.1 M–HCl extractable fractions of lead at the roadside area are significantly higher than those obtained at the residential area, especially for the coarse mode of the particulate samples. Moreover, the solubility characteristics of the roadside particulate lead have partially overlapped with those of the road dust samples. The XANES spectra for coarse mode of particulate lead also nearly correspond to that of the road dust collected around the roadside area. These results indicate effects by the re–suspension of road dust to the roadside air. However, it is difficult to clear the roadside contamination from specific lead material applied in this study. This might suggest that specific lead compounds do not exist exclusively in atmospheric particles but exist as mixtures or unknown complexes.

Mechanism of PM2.5 Filter Grouped by Micro-nano Wood Wool Flour

Aiming at the problem of Suspended particles filter difficult in the air at present, this paper putted forward the goal of using micron wood wool and micro and nano wood flour to group PM2.5 filter, which used filter material of wood natural environmental and cavities adsorbing function in its natural structure after carbonization to filter atmospheric suspended particles, such as automobile exhaust, coal particles, and so on. This paper analyzed filter at home and abroad, and putted forward to filtering mechanism and technology roadmap of wood-based ecological level anion PM2.5 filter. Through the feasibility demonstrated, it would propose a research direction of wood-based materials as an air filter.

Observation of NO3 radicals over Shanghai, China

Observation of NO3 radicals was performed in an urban area of Shanghai using differential optical absorption spectroscopy from August 15 to October 7, 2011. With the exception of the data below detection limit (0.008 ppb), the observed mean NO3 mixing ratios were 0.016 ± 0.009 ppb with a range of 0.008–0.095 ppb. Under the assumption of steady state, the NO3 production rates were calculated ranging from 0.08 ppb h−1 to 12.85 ppb h−1 throughout the observation, and averaged at 1.10 ± 1.09 ppb h−1. The calculated NO3 lifetime was determined from several seconds to a maximum value of about 900 s with an average of 102 ± 93 s. The correlation of NO3 production rates to the NO2 mixing ratio is about 0.76, which is larger than the correlation between NO3 production rates and O3. Hence, the variability of NO3 production mainly results from the ambient NO2 levels present. The positive correlation between the NO3 mixing ratio and its production rates indicates that direct sinks cannot be neglected for the nitrate radical's chemistry in Shanghai, especially under polluted conditions. However, the slope of the logarithmic correlation between NO3 lifetime and NO2 mixing ratio is very close to −1, which means that the NO3 removal strongly depends on the indirect loss process. Moreover, the atmospheric suspended particles have an important impact on NO3 lifetime because the NO3 removal was accelerated by the high PM10 concentration, e.g. all NO3 lifetime are below 30 s when the PM10 concentration was larger than 0.05 mg m−3 during the severe pollution episode in October.

Characteristics of atmospheric suspended soil particles in the Asian dust-storm period in Kobe city

Characteristics of atmospheric suspended soil particles in the Asian dust-storm period in Kobe city

Total mercury in terrestrial systems (air-soil-plant-water) at the mining region of San Joaquín, Queretaro, Mexico

Deficient management of cinnabar mining left the San Joaquín region with high concentrations of mercury in its soils (2.4 – 4164 mg kg-1). Numerous cinnabar mines have contributed to the dispersion of mercury into agricultural (0.5 –314 mg kg-1) and forest (0.2 – 69 mg kg-1) soils. Sediments are a natural means of transportation for mercury, causing its spreading, especially in areas near mine entrances (0.6 – 687 mg kg-1). The nearness of maize crops to mines favors mercury accumulation in the different plant structures, such as roots, stems, leaves, and grain (0.04 – 8.2 mg kg-1); these being related to mercury volatilization and accumulation in soils. Mercury vapor present in the settlements could indicate a constant volatilization from lands and soils (22 – 153 ng m-3). The mercury levels found in the soils, in maize grain, and in the air resulted greater than the standards reported by the Official Mexican Norm (NOM) and the World Health Organization (WHO). Mercury in rainwater is due mainly to the presence of suspended atmospheric particles, later deposited on the surface (1.5 – 339 μg |-1). Mercury dissolution was found in the drinking water (10 – 170 ng |-1), with concentrations below those established by the NOM and the WHO. The contamination existing in the San Joaquín region does not reach the levels of the world’s greatest mercury producers: Almaden (Spain) and Idrija (Slovenia). It is, however, like that found in other important second degree world producers such as Guizhou (China). The population of San Joaquín, as well as its surrounding environment, are constantly exposed to mercury contamination, thus making a long term monitoring necessary to determine its effects, especially to people.